Random Regret Minimization and Random Utility Maximization in the Presence of Preference Heterogeneity: An Empirical Contrast

Abstract

Random regret minimisation (RRM) interpretations of discrete choices are growing in popularity as a complementary modelling paradigm to random utility maximisation (RUM). While behaviourally very appealing in the sense of accommodating the regret of not choosing the ‘best’ alternative, studies to date suggest that the differences in willingness to pay estimates, choice elasticities and choice probabilities compared to RUM are small. However, the evidence is largely based on a simple multinomial logit form of the RRM model. In this paper we revisit this behavioural contrast and move beyond the multinomial logit model to incorporate random parameters, revealing the presence of preference heterogeneity. The important contribution of this paper is to see if the extension of RRM‐MNL to RRM‐mixed logit in passenger mode choice widens the behavioural differences between RUM and RRM. The current paper has identified a statistically richer improvement in fit of mixed logit compared to multinomial logit under RRM (and RUM) but found small differences overall between the empirical outputs of RUM and RRM, with no basis of an improved model fit between these two non‐nested model forms. The inclusion of both model forms should continue to inform the likely range of behavioural outputs as we investigate a broader range of process heuristics designed to capture real world behavioural response.